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Scalable and flexible clustering solutions for mobile phone-based population indicators

Overview of attention for article published in International Journal of Data Science and Analytics, July 2017
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1 X user

Citations

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6 Dimensions

Readers on

mendeley
13 Mendeley
Title
Scalable and flexible clustering solutions for mobile phone-based population indicators
Published in
International Journal of Data Science and Analytics, July 2017
DOI 10.1007/s41060-017-0065-y
Authors

Alessandro Lulli, Lorenzo Gabrielli, Patrizio Dazzi, Matteo Dell’Amico, Pietro Michiardi, Mirco Nanni, Laura Ricci

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 31%
Student > Ph. D. Student 3 23%
Researcher 2 15%
Professor 1 8%
Lecturer 1 8%
Other 1 8%
Unknown 1 8%
Readers by discipline Count As %
Computer Science 6 46%
Arts and Humanities 1 8%
Economics, Econometrics and Finance 1 8%
Earth and Planetary Sciences 1 8%
Social Sciences 1 8%
Other 1 8%
Unknown 2 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 July 2017.
All research outputs
#15,855,488
of 23,560,187 outputs
Outputs from International Journal of Data Science and Analytics
#1
of 1 outputs
Outputs of similar age
#200,545
of 317,737 outputs
Outputs of similar age from International Journal of Data Science and Analytics
#1
of 1 outputs
Altmetric has tracked 23,560,187 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1 research outputs from this source. They receive a mean Attention Score of 0.0. This one scored the same or higher as 0 of them.
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We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them